---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-indian-food
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# finetuned-indian-food

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2562
- Accuracy: 0.9299

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0023        | 0.3003 | 100  | 0.9838          | 0.8183   |
| 0.6632        | 0.6006 | 200  | 0.6198          | 0.8682   |
| 0.6017        | 0.9009 | 300  | 0.5164          | 0.8884   |
| 0.4634        | 1.2012 | 400  | 0.4615          | 0.8895   |
| 0.4579        | 1.5015 | 500  | 0.4084          | 0.8969   |
| 0.4473        | 1.8018 | 600  | 0.4043          | 0.8948   |
| 0.2992        | 2.1021 | 700  | 0.3623          | 0.8980   |
| 0.2645        | 2.4024 | 800  | 0.3327          | 0.9139   |
| 0.2166        | 2.7027 | 900  | 0.3242          | 0.9171   |
| 0.2273        | 3.0030 | 1000 | 0.2986          | 0.9203   |
| 0.2527        | 3.3033 | 1100 | 0.3150          | 0.9150   |
| 0.2265        | 3.6036 | 1200 | 0.2596          | 0.9277   |
| 0.1046        | 3.9039 | 1300 | 0.2562          | 0.9299   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1